spectral emissivity and temperature maps of the solfatara ... · solfatara is a volcanic crater...
TRANSCRIPT
Spectral emissivity and temperature maps of the Solfatara crater from
DAIS hyperspectral images
Luca Merucci(1), Maria Paola Bogliolo(2), Maria Fabrizia Buongiorno(1) and Sergio Teggi(3)
(1) Istituto Nazionale di Geofisica e Vulcanologia, Roma, Italy
(2) Istituto Superiore per la Prevenzione e la Sicurezza del Lavoro, Monteporzio Catone (RM), Italy
(3) Università di Modena e Reggio Emilia, Modena, Italy
Abstract
Quantitative maps of surface temperature and spectral emissivity have been retrieved on the
Solfatara crater at Pozzuoli (Naples) from remote sensing hyperspectral data. The present study
relies on thermal infrared images collected on July 27, 1997 by the DAIS hyperspectral sensor,
owned by the German aerospace center (DLR). The Emissivity Spectrum Normalization method
was used to make temperature and emissivity estimates. Raw data were previously transformed in
radiance and corrected for the atmospheric contributes using the MODTRAN radiative transfer code
and the sensor response functions. During the DAIS flight a radiosonde was launched to collect the
atmospheric profiles of pressure, temperature and humidity used as input to the code. Retrieved
temperature values are in good agreement with temperature measures performed in situ during the
campaign. The spectral emissivity map was used to classify the image in different geo-
mineralogical units with the Spectral Angle Mapper method. Areas of geologic interest were
previously selected using a mask obtained from an NDVI image calculated with two channels of the
visible (red) and the near infrared respectively.
Key words: hyperspectral data - surface temperature - spectral emissivity –Solfatara (Phlegraean
Fields) - DAIS
1. Introduction
Surface temperature and spectral emissivity of materials are valuable parameters in volcanology,
since they provide information on several aspects of the current activity and of past events.
Mapping surface temperature allows to estimate the heath flux from the surface and therefore to
control activity inside vents and fractures. Spectral emissivity in the thermal infrared is a physical
parameter necessary to calculate temperature, and moreover it enables recognition of surface
materials on the basis of their spectral pattern (Salisbury and D’Aria, 1992); it is particularly
suitable to study volcanic materials, because the main absorption bands of silicates are located in
the thermal infrared (Gillespie, 1985). Remote separation and identification of surface deposits in
volcanic areas is useful to map lava flows on the basis of their composition, to characterize surface
alteration due to hydrothermal phenomena, and to identify newly formed deposits related to
fumarolic activity.
Surface kinetic temperature and emissivity properties of materials can be estimated with high
accuracy by remote sensing, if images collected on several channels in the thermal infrared are
available. Thermal infrared multi-channel sensors have been operating for long time at low spatial
resolution (less than one km, mainly for meteorological or oceanographic use), and only few
instruments provide multi-channel images at high spatial resolution in this spectral range. The
airborne hyperspectral sensors TIMS (NASA), MIVIS (CNR – L.A.R.A. Project) and DAIS
(German aerospace center DLR) and the spaceborne sensor ASTER, onboard on TERRA and
AQUA satellites (NASA) are examples of this kind of instruments.
With the aim of understanding capabilities of the DAIS (Digital Airborne Imaging Spectrometer)
hyperspectral sensor to provide information of volcanological interest, we analyzed the thermal
infrared DAIS data of an active volcanic area, according to three work phases: 1) retrieval of the
radiance emitted by the surface, through atmospheric modeling; 2) estimation of surface
temperature and spectral emissivity; 3) application of spectral mapping techniques to produce a
thematic map of the main surface units.
2. Data Set
Remote sensing data used in this study were provided by the DAIS 7915 spectrometer, owned by
the German aerospace center (DLR). Main spectral and technical characteristics of DAIS are
summarized in table I. The image under investigation was collected on July 27, 1997 at 10:27 (local
time) on the Solfatara crater at Pozzuoli (Naples, Italy), in the framework of the E.C. Large Scale
Facilities Project, and under request and supervision of the Remote Sensing Laboratory of the
Italian National Institute of Geophysics and Volcanology (INGV) of Rome. DAIS was flown on a
DO 228 aircraft at an altitude of 1600 m a.s.l., and the collected images ground resolution is about 5
meters. The data spectral subset used here corresponds to the six DAIS infrared thermal channels.
Simultaneously with the DAIS flight, a ground measurement campaign was carried out to measure
the parameters necessary to atmospheric correction and validation of the retrieved maps. Vertical
atmospheric profiles of pressure, temperature and relative humidity at about 10 meters vertical
resolution were measured by means of a radiosonde launch performed near the Solfatara (fig. 1).
Surface brightness temperature was measured with an infrared thermometer (EVEREST Inters.
Inc.) at different sites (fig. 1), selected on homogeneous and horizontal surfaces easy to locate on
the images. In order to compensate for the spatial scale difference between the ground measures and
the remote sensing data, 10 measurements were acquired on different points at each site: the
average value was considered to be representative of the site brightness temperature. Temperature
inside fumaroles was also measured with a thermocouple.
3. Geological setting
Solfatara is a volcanic crater located in the central area of the Phlegraean Fields caldera complex,
west of the city of Naples (Italy) (fig. 2, 3). It represents the most active zone of Phlegraean Fields,
and sits inside the sprawling urban area of Pozzuoli.
Activity in the Phlegraean area has been dominated by two eruptions that produced widespread ash-
flow deposits: the Campanian Ignimbrite and the smaller Neapolitan Yellow Tuff (Lirer et al.,
1987; Scandone et al., 1991). The eruption producing the Campanian Ignimbrite occurred 37.000
years b.p. and resulted in the collapse of a large area including Campi Flegrei and part of the gulf of
Naples. The eruption of Neapolitan Yellow Tuff occurred 12.000 years b.p, had a very complex
history that led to the formation of a caldera of smaller dimensions inside that of the Campanian
Ignimbrite. In the last 12.000 years, the bottom of the Neapolitan Yellow Tuff caldera has been seat
of intense volcanic activity and ground deformation (Di Vito et al., 1998). Volcanism was
concentrated in three periods: 12.000 and 9.500 years b.p., 8.600 and 8.200 years b.p., and 4.800
and 3.800 years b.p. (e.g. at Cigliano, Agnano - Monte Spina, Astroni, Averno, Solfatara), followed
by the last eruption in 1538 that brought to the formation of the Monte Nuovo (Di Vito et al., 1987).
Since 1800, sea-level measurements made at ancient roman ruins have indicated a slow sinking of
the area. This slow sinking of the ground continued until 1968. In the periods 1970-1972 and 1982-
1984 two important bradyseismic events (ground uplift) occurred in the Pozzuoli area (Corrado et
al., 1976; Berrino et al., 1984), (maximum uplift of 1.7 and 1.8 m respectively) accompanied by
shallow seismicity. More recently, two minor sudden ground uplifts and seismic swarms were
recorded in 1989-90 and in 1994.
The Solfatara volcano is one of the most recent (about 4.000 years b.p.) of the Phlegraean Fields
caldera. It has a dimension of 0.5 x 0.6 km, with steep walls on the north, east, and south sides. To
the west the crater wall is missing. Its rectangular shape is mostly due to the presence of faults at
NW-SE and S W- N E . The volcanic cone is made of pyroclastic rocks, with the exception of Mt.
Olibano that is a dome of trachytic lava.
The flat-floored crater (Piano Sterile) is characterized by strong fumarolic activity which causes
both single vent emissions, with temperature up to 160°C, and diffuse degassing. The gases emitted
are mostly composed by H2O, CO2, H2S and smaller quantities of H2, CH4, He, HCl, Ar (Valentino
et al., 1999).
One of the most recent hydrothermal models (Chiodini et al., 1997) describes a system divided in
three parts: 1) a heat source which is made up of a relatively shallow magmatic chamber; 2) one or
more aquifers located above the chamber; the degassing magma supplies fluids and heat to them; 3)
an intensely fractured zone, sited above the uppermost aquifer and occupied by a pure vapor phase,
which is produced through boiling of the underlying aquifers.
The intense fumarolic activity has given origin to strong hydrothermal alteration of the original
rocks (De Gennaro et al., 1980) and to secondary deposits. In fact, the trachytic rocks of the floor
and of the flanks of the volcano are bleached and corroded by the effluent vapours, with formation
of gypsum, alum, kaolin and alunite (Valentino et al., 1999). Moreover, sublimation of the emitted
gas causes deposition of sulphur, arsenic sulphide (realgar), ammonium chloride (sal ammoniac),
mercury sulphide, antimony sulphide.
4. Atmospheric correction
The spectral radiance LD received by a remote sensor in the thermal infrared can be expressed as:
( )[ ] )()()()(1),()()( λλτλλελλελ udsD LLTBL +⋅⋅−+⋅= [1]
where: Lu is the upward atmospheric radiance, Ld is the downward atmospheric radiance, Ts is the
surface kinetic temperature, ε is the surface emissivity, τ is the atmospheric transmittance between
the surface and the sensor, and B(Ts) is the Plank function.
In order to calculate the radiance emitted by the surface ( ( ) ( ) ( )ss TBTL ,, λλελ ⋅= ), remote sensing
data must be corrected for atmospheric effects. To estimate the atmospheric radiative contributes
(Lu, Ld and τ), we used the MODTRAN 3.5 radiative transfer code (Berk et al., 1989), giving as
input the atmospheric profiles measured during the field campaign. The obtained values were
convolved with the sensor response functions of the six thermal infrared channels (fig. 4).
The atmospheric terms were estimated for 20 different optical paths corresponding to view angles
increments of ≈3° with respect to the nadir. Lower angle increments result into neglectable
variations. The different sets of atmospheric terms were used to apply separate corrections on image
stripes corresponding to the view angle increments and parallel to the image axis.
5. Evaluation of surface temperature and emissivity
The spectral radiance emitted by a body having a kinetic temperature Ts can be expressed as a
function of the spectral emissivity ε of its surface and of the Plank function B:
( ) ( ) ( )ss TBTL ,, λλελ ⋅= [2]
If the radiance L is measured at N wavelengths λ, the relation is expressed by a system of N
equations with N+1 unknowns, i.e. the N values of spectral emissivity and the temperature.
This makes difficult the estimation of surface temperature and emissivity from remote sensing data
because the equation system is not closed. In the literature, different “non-exact” solutions are given
to this problem, called “temperature and emissivity separation” (Gillespie et al., 1998; Li et al.,
1999).
In our work we applied the well established method of the Emissivity Spectrum Normalization
(ESN) (Gillespie, 1985; Realmuto, 1990). According to this method, emissivity is normalized to a
value εmax corresponding to the maximum value expected in the scene. This method demonstrated
good capability to maintain the spectrum shape, that is the most important feature in applications of
spectral analysis and mapping.
Assuming ε = εmax for each value of λ, the inversion of Eq. 2 gives N values of temperature; the
highest of them is assumed to be the estimate of the kinetic temperature Ts. With this value, and
using the Plank equation, the black body spectral radiance of the pixel is calculated. Finally, the
emissivity is obtained dividing the surface radiance measured by the sensor by the calculated black
body radiance, at each wavelength. Repeating this procedure for every pixel, temperature and
spectral emissivity maps are obtained. In this study we assumed a value εmax = 0.97 on the basis of
the spectral libraries data (Salisbury, J. W. et al., 1991; Salisbury and D’Aria, 1992) available for
the typical minerals of the Solfatara crater .
6. Selection of the areas of interest
The atmospheric correction and the temperature and emissivity estimation were performed on an
image window chosen in correspondence of the Solfatara crater.
Urban areas adjacent to the Solfatara have been excluded applying a suitable mask cropped on the
original image. On these areas reliable estimates of surface temperature and spectral emissivity
cannot be obtained by the ESN method due to the urban covers extreme heterogeneity that makes it
impossible to define a value of εmax valid for the whole image. Moreover, the estimated surface
temperature can be considered validated only inside the crater, where the in situ temperature has
been measured during the ground campaign.
In the images showing the elaboration results (fig. 5, 6 and 8), non-processed areas have been
masked with an image of a thermal channel to preserve topographic reference.
A further selection was applied to identify the areas of interest for geo-mineralogical interpretation:
the vegetation cover was excluded with a mask based on the normalized difference vegetation index
(NDVI). The data of two channels of visible (red) and near infrared, are transformed by NDVI in a
new image related to the green biomass using a spectral property of green vegetation: the sharp
increase of reflectance between 0.65 and 0.80 µm (red edge).
The NDVI image was obtained using the DAIS channels 10 (0.659 µm) and 18 (0.802 µm); it was
then converted in a mask by selecting a threshold value between vegetated and non vegetated
pixels.
7. Results
Fig. 5 shows the quantitative map of surface kinetic temperature. Values retrieved in
correspondence of the ground measurement sites (fig. 1) were extracted from this map and
compared with ground temperatures: the comparison revealed a good agreement, as shown in table
II.
The six images of spectral emissivity allowed to discriminate different surface covers on the basis
of their spectral characteristics. An example is reported in fig. 6, where an RGB composition of
spectral emissivity calculated in channels 78, 76 and 74 is reported.
By analyzing the emissivity images and the corresponding spectra, we could discriminate 6 main
units, which spectra strongly differ each other. Fumarolic fields are well separable since they have a
very distinctive spectral pattern, and materials with different emissive properties are recognizable,
probably corresponding to different degrees of hydrothermal alteration of the surface and to
depositions from fumarolic gases. An example of the emissivity spectra of the separated units is
reported in fig. 7.
Spectral information retrieved from the emissivity images was used to produce a map of the main
geo-mineralogical units outcropping at the Solfatara crater, applying the Spectral Angle Mapper
(SAM) technique (Kruse et al., 1993) (fig. 8). SAM is a physically-based spectral classification that
uses an n-dimensional angle to match pixels to reference spectra (end-members). The algorithm
determines the spectral similarity between two spectra by calculating the angle between the spectra,
treating them as vectors in a space with dimensionality equal to the number of bands (RSI, 2002).
Non-processed areas and zones covered by vegetation were previously masked as already
described. Pure spectra required by this technique were obtained averaging spectra of little groups
of pixels, selected on the image on the basis of information drawn from field survey and spectral
analysis (fig. 7).
The six units detected were only separated but not yet identified at this stage of the work: to do this,
representative emissivity measurements are needed to be compared with image spectra. Emissivity
spectra of surface materials are strongly influenced by various factors (Salisbury and D’Aria, 1992),
such as granulometry, temperature, compaction level, water content; in a remote sensing scene,
pixel spectra are also influenced by local un-homogeneities of the deposits. For these reasons, a
direct comparison between image spectra and reference spectra of minerals from public spectral
libraries is not feasible; field measurements of spectral emissivity are required to perform reliable
comparisons.
8. Conclusions and future work
DAIS thermal infrared data were used to retrieve surface temperature ad spectral emissivity maps of
the Solfatara crater. Our results confirm DAIS capability to provide valuable volcanological
information based on the thermal infrared properties of materials. The quantitative temperature map
of the area that we have obtained allows to locate thermal anomalies corresponding to active
fumaroles and to characterize their thermal properties. The spectral emissivity image allows the
mapping of the main geo-mineralogical units on the basis of their spectral properties. This thematic
map points out that six thermal infrared channels are sufficient to detect and separate not only
different surface covers but also alike materials whose differences are mainly related to their
alteration degree.
In order to complete the image interpretation and perform the automatic identification of the
classes, field acquisition of emissivity spectra is planned. Spectral emissivity will be measured with
a portable FTIR (Fourier Transform InfraRed) spectrometer (Design & Prototypes LTD), working
in the 2 – 16 µm spectral range with a spectral resolution between 2 and 16 cm-1. Sampled materials
will be analyzed in the laboratory to retrieve chemical and mineralogical features corresponding to
the field collected spectra.
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Tables
Table I. DAIS 7915 main technical and spectral characteristics. Spectrometer Spectral region N. of
channels Wavelength
1 0.4-1.0 µm 32 15-30 nm 2 1.5-1.8 µm 8 45 nm
3 2.0-2.5 µm 3.0-5.0 µm
32 1
20 nm 2.0 µm
4 8.0-12.6 µm 6 0.9 µm Dynamic range 15 bit
Ground resolution 5 – 20 m (function of the flight altitude) Scan line dimension 512 pixels
Table II. Comparison between ground measured temperature and image retrieved temperature at the sites shown in fig. 1.
Site Measurement start / end (local time)
Ground temperature (°C)
Image retrieved temperature (°C)
Fumarole; dark grey soil (1FF) 11.10 / 11.15 45.18 ± 4.31 44.2 Central area (1CA) 11.20 / 11.25 44.91± 2.60 42.7 White tuffs (1WT) 11.30 /11.31 37.18 ± 0.24 36.9 Campground (2CG) 10.40 / 10.43 44.54 ± 1.87 42.7 Dry grass (2DG) 10.45 / 10.50 54.71± 3.31 50.7 Tuffs (2T) 10.55 /11.00 42.32 ± 2.32 40.0
Figure Captions
Fig. 1. Topographic map of the Solfatara crater. Gray squares indicate the surface temperature
measurement sites; the black circle (RS) locates the radiosonde launch site.
Fig. 2. Schematic geological map of the Phlegraean Fields (Scandone, 1997).
Fig. 3. Solfatara crater at Pozzuoli (Naples, Italy). Picture from Pozzuoli dal cielo by Aeromap
Data.
Fig. 4. Response functions of the DAIS thermal infrared channels.
Fig. 5. Surface temperature map of the Solfatara crater retrieved by DAIS data.
Fig. 6. Spectral emissivity image in DAIS channels 78-76-74 (RGB).
Fig. 7. Emissivity spectra retrieved from the DAIS data. Average values were calculated on regions
of interest selected on the main surface units.
Fig. 8. Map of the main geo-mineralogical units outcropping at the Solfatara crater.
Fig. 1
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